The world of tomorrow is a terrifying place – looks like we have some tidying-up to do.
Recently I was asked to take a look at two articles related to Twitter bots. Rob Dubbin’s The Rise of Twitter Bots was a more relaxed take on the subject: Twitter bots represent a long spanning gamut between wasting time and a reminder of surveillance. The other, Mark Sample’s piece on protest bots, looked to take a deeper look into how to effectively create protest on the internet by arming bots with more than just simple repetitions, but rather intricate creations of an uncanny environment that captures attention. Twitter has graciously opened their API for development which made all of these creative and powerful ventures possible, but we should rather look towards the future of Twitter bots, specifically how artificial intelligence will affect a platform like this.
Continue reading “Twitter Bots: Useful, Dangerous, or Both”
Finnegans Wake can now haunt the academic in their sleep, and on their twitter feed.
Continue reading “Finnegans Ache: The Worst Twitter Bot Ever Created”
Who knew that Finnegans Wake would one day be reduced to cells in a spreadsheet?
For a long time, I wanted to do experiments with Finnegans Wake and data visualizations. A recent assignment gave me this chance, so I quickly got to work. The first thing I had to do was figure out my dataset. Obviously Finnegans Wake is fiction and relies heavily on an idioglossia of Joyce’s design so it might be tough to pinpoint distinct data points for the book. This meant that I had to take a step back and look at the book from a very removed perspective to start -what better a dataset for this book than its own lexicon and frequencies? Studying the Wake in the past led me to remember a couple of different online tools like Fweet, which is a search engine for the book, and Finwake which is an online annotated version. However, the most useful gathered data would have to be from Eric Rosenbloom’s Concordance of Finnegans Wake which he compiled apparently in the late 1990s. Throughout this project, there will definitely be certain data constraints considering the fact that no major datasets have really been constructed for the Wake.
Continue reading “Wakeipedia: Experimenting with Finnegans Wake Data”
In the past I used MTurk because my brother found it to be a decent money maker back when he was in high school in 2008. I was curious after doing class readings to revisit Amazon Mechanical Turk and see what’s new on the platform. When I first logged on, I noticed that my hit history was available: 17 hits submitted for a grand total of $12.20. It probably took me at least a couple of hours to make it that far. During our reading, we learned about the harsh realities of MTurk where 52% of users make less than 5 dollars an hour.
Continue reading “Returning to MTurk: It’s Still Impossible to Make Money”